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Record W4308572081 · doi:10.1159/000527540

EASO and EFAD Position Statement on Medical Nutrition Therapy for the Management of Overweight and Obesity in Children and Adolescents

2022· review· en· W4308572081 on OpenAlexaff
Maria Hassapidou, Kerith Duncanson, Vanessa A. Shrewsbury, Louisa Ells, Hilda Mulrooney, Odysseas Androutsos, Antonis Vlassopoulos, Ana Isabel Rito, Nathalie Farpourt, Tamara Brown, Pauline Douglas, Ximena Ramos Sallas, Euan Woodward, Clare E. Collins

Bibliographic record

VenueObesity Facts · 2022
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsCanadian Obesity NetworkUniversity of Alberta
Fundersnot available
KeywordsMedicineOverweightPsychological interventionPosition statementObesityRandomized controlled trialSystematic reviewIntervention (counseling)Weight managementEnvironmental healthMedical nutrition therapyFamily medicineGerontologyMEDLINEPhysical therapyIntensive care medicineNursingSurgeryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: This position statement on medical nutrition therapy in the management of overweight or obesity in children and adolescents was prepared by an expert committee convened by the European Association for the Study of Obesity (EASO) and developed in collaboration with the European Federation of the Associations of Dietitians (EFAD). METHODS: It is based on the best evidence available from systematic reviews of randomized controlled trials on child and adolescent overweight and obesity treatment and other relevant peer-reviewed literature. RESULTS: Multicomponent behavioural interventions are generally considered to be the gold standard treatment for children and adolescents living with obesity. The evidence presented in this position statement confirms that dietary interventions can effectively improve adiposity-related outcomes. Dietary strategies should focus on the reduction of total energy intake through promotion of food-based guidelines that target modification of usual eating patterns and behaviours. These should target increasing intakes of nutrient-rich foods with a lower energy density, specifically vegetables and fruits, and a reduction in intakes of energy-dense nutrient-poor foods and beverages. In addition, higher intensity, longer duration treatments, delivered by interventionists with specialized dietetic-related skills and co-designed with families, are associated with greater treatment effects. DISCUSSION: Such interventions should be resourced adequately so that they can be implemented in a range of settings and in different formats, including digital or online delivery, to enhance accessibility.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0040.003
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0080.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.313
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2022
Admission routes1
Has abstractyes

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